• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.133-144
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• 2020

The number of elderly people with dementia is increasing as fast as the proportion of older people due to aging, which creates a social and economic burden. In particular, dementia care costs, including indirect costs such as increased care costs due to lost caregiver hours and caregivers, have grown exponentially over the years. In order to reduce these costs, it is urgent to introduce a management system to care for dementia patients. Therefore, this study proposes a sensor-based abnormal behavior detection system to manage dementia patients who live alone or in an environment where they cannot always take care of dementia patients. Existing studies were merely evaluating behavior or evaluating normal behavior, and there were studies that perceived behavior by processing images, not data from sensors. In this study, we recognized the limitation of real data collection and used both the auto-encoder, the unsupervised learning model, and the LSTM, the supervised learning model. Autoencoder, an unsupervised learning model, trained normal behavioral data to learn patterns for normal behavior, and LSTM further refined classification by learning behaviors that could be perceived by sensors. The test results show that each model has about 96% and 98% accuracy and is designed to pass the LSTM model when the autoencoder outlier has more than 3%. The system is expected to effectively manage the elderly and dementia patients who live alone and reduce the cost of caring.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.231-242
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• 2004

Remote control and monitoring of information appliances require RTOS and TCP/IP network module to communicate each other. Traditional TCP/IP protocol stacks, however, require relatively large resources to be useful in small 8 or 16-bit systems both in terms of code size and memory usage. It motivates design and implementation of micro TCP/IP that is lightweight for embedded systems. Micro embedded web server is also required to control and monitor information appliances through the Web. In this paper, we design and implement micro TCP/IP and Web server for information appliances. For this goal, we investigate requirements for the interoperability of embedded systems with the Internet and the Web-based control of embedded systems. Next, we compare our micro TCP/IP protocol stack with that of RTIP and QPlus in terms of object code size and performance. The size of micro TCP/IP protocol stack can be reduced by 3/2 and 1/4, respectively, comparing with that of RTIP and QPlus. We also show that the performance of our micro TCP/IP is similar to that of RTIP and QPlus since it handles 2.9Mbps when delayed ACK is not adapted.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.105-112
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• 2017

PCI Express is a bus technology that connects the processor and the peripheral I/O devices that widely used as an industry standard because it has the characteristics of high-speed, low power. In addition, PCI Express is system interconnect technology such as Ethernet and Infiniband used in high-performance computing and computer cluster. PGAS(partitioned global address space) programming model is often used to implement the one-sided RDMA(remote direct memory access) from multi-host systems, such as computer clusters. In this paper, we design and implement a OpenSHMEM API based on PCI Express maintaining the existing features of OpenSHMEM to implement RDMA based on PCI Express. We perform experiment with implemented OpenSHMEM API through a matrix multiplication example from system which PCs connected with NTB(non-transparent bridge) technology of PCI Express. The PCI Express interconnection network is currently very expensive and is not yet widely available to the general public. Nevertheless, we actually implemented and evaluated a PCI Express based interconnection network on the RDK evaluation board. In addition, we have implemented the OpenSHMEM software stack, which is of great interest recently.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.13-18
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• 2014

Sensor nodes are used for monitoring and collecting the environmental data via wireless sensor network. The wireless sensor network with various sensor nodes draws attention as a key technology in ubiquitous computing. Sensor nodes has very small memory capacity and limited power resource. Thus, it is essential to have energy efficient strategy for the sensor nodes. Since the sensor nodes are operating on the same frequency bands with ISM frequency bands, the interference by the devices operating on the ISM band degrades the quality of communication integrity. In this paper, the convolutional code is proposed instead of ARQ for the error control for the sensor network. The proposed convolutional code was implemented and the BER performance is measured. For the fixed transmitting powers of -19.2 dBm and -25dBm, the BER with various communication distances are measured. The packet loss rate and the retransmission rate are calculated from the measured BER. It is shown that the porposed method obtained about 9~12% and 12-19% reduction in retransmission rate for -19.2 dBm and -25 dBm respectively.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.125-132
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• 2014

Since frequent pattern mining was proposed in order to search for hidden, useful pattern information from large-scale databases, various types of mining approaches and applications have been researched. Especially, frequent graph pattern mining was suggested to effectively deal with recent data that have been complicated continually, and a variety of efficient graph mining algorithms have been studied. Graph patterns obtained from graph databases have their own importance and characteristics different from one another according to the elements composing them and their lengths. However, traditional frequent graph pattern mining approaches have the limitations that do not consider such problems. That is, the existing methods consider only one minimum support threshold regardless of the lengths of graph patterns extracted from their mining operations and do not use any of the patterns' weight factors; therefore, a large number of actually useless graph patterns may be generated. Small graph patterns with a few vertices and edges tend to be interesting when their weighted supports are relatively high, while large ones with many elements can be useful even if their weighted supports are relatively low. For this reason, we propose a weight-based frequent graph pattern mining algorithm considering length-decreasing support constraints. Comprehensive experimental results provided in this paper show that the proposed method guarantees more outstanding performance compared to a state-of-the-art graph mining algorithm in terms of pattern generation, runtime, and memory usage.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.126-131
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• 2015

As flash-based storage systems have been actively employed in large-scale servers and data centers, reliability has become an indispensable element. One promising technique for enhancing reliability is static wear-leveling, which distributes erase operations evenly among blocks so that the lifespan of storage systems can be prolonged. However, increasing the capacity makes the processing overhead of this technique non-trivial, mainly due to searching for blocks whose erase count would be minimum (or maximum) among all blocks. To reduce this overhead, we introduce a new randomized block selection method in static wear-leveling. Specifically, without exhaustive search, it chooses n blocks randomly and selects the maximal/minimal erased blocks among the chosen set. Our experimental results revealed that, when n is 2, the wear-leveling effects can be obtained, while for n beyond 4, the effect is close to that obtained from traditional static wear-leveling. For quantitative evaluation of the processing overhead, the scheme was actually implemented on an FPGA board, and overhead reduction of more than 3 times was observed. This implies that the proposed scheme performs as effectively as the traditional static wear-leveling while reducing overhead.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.13-24
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• 2003

MPEG-4 is a standard for multimedia applications and provides a set of technologies to satisfy the needs of authors, service providers and end users alike. In this paper, we suggest a Real-time Multiple Circular Buffer (M4RM Buffer) model, which is suitable for streaming these MPEG-4 contents efficiently. M4RM buffer generates each structure of the buffer, which matches well with each object composing an MPEG-4 content, according to the transferred information, and manipulates multiple read/write operations only by its reference. It divides the decoder buffer and the composition buffer, which are described in the standard, by the unit of frame allocated to minimize the range of access. This buffer unit of a frame is allocated according to the object description. Also, it processes the objects synchronization within the buffer and provides APIs for an efficient buffer management to process the real-time user events. Based on the performance evaluation, we show that M4RM buffer model decreases the waiting time in a buffer frame, and so allows the real-time streaming of an MPEG-4 content using the smaller size of the memory block than IM1-2D and Window Media Player.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.3
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• pp.240-247
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• 2001

Java is a promising runtime environment for embedded systems because it has many advantages such as platform independence, high security and support for multi-threading. One of the most famous Java run-time environments, Sun's ($PersonalJave^{TM}$) is based on Truffle architecture, which enables programmers to design various GUIs easily. For this reason, it has been ported to various embedded systems such as set-top boxes and personal digital assistants(PDA's). Basically, Truffle uses heavy-weight window managers such as Microsoft vVin32 API and X-Window. However, those window managers are not adequate for embedded systems because they require a large amount of memory and disk space. To come up with the requirements of embedded systems, we adopt Microwindows as the platform graphic system for Personal] ava A WT onto Embedded Linux. Although Microwindows is a light-weight window manager, it provides as powerful API as traditional window managers. Because Microwindows does not require any support from other graphics systems, it can be easily ported to various platforms. In addition, it is an open source code software. Therefore, we can easily modify and extend it as needed. In this paper, we implement Personal]ava A WT using Microwindows on embedded Linux and prove the efficiency of our approach.